• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.23 no.8
• /
• pp.14-20
• /
• 2009

In this paper, the time-varying failure rate to consider climate effect was extracted. Even if the same kind of equipments is estimated for extracting the time-varying failure rate, the failure rates could be different depending on external effect such as climate. With the consequence, the failure rate extracted to consider the climate effect is necessary for using the failure rate on the optimal investment plan or asset management, To consider the characteristic of climate effects(Classified into 5 categories, heavy rain, thunderbolt, strong wind, tidal waves, no character), the survey of officers charging the operation of equipment in KEPCO branch office was done. With this consequence, this paper suggest the failure rate extraction method to consider the climate effect analyzed by the survey.

• Communications for Statistical Applications and Methods
• /
• v.23 no.4
• /
• pp.335-341
• /
• 2016

Interval censored failure time data often occurs in an observational study where a subject is followed periodically. Instead of observing an exact failure time, two inspection times that include it are made available. Several methods have been suggested to analyze interval censored failure time data (Sun, 2006). In this article, we are concerned with a binary time-varying covariate whose changing time is interval censored. A modified estimating equation is proposed by extending the approach suggested in the presence of a missing covariate. Based on simulation results, the proposed method shows a better performance than other simple imputation methods. ACTG 181 dataset were analyzed as a real example.

• Proceedings of the KIEE Conference
• /
• 2006.11a
• /
• pp.9-11
• /
• 2006

This paper suggests a revision method for historical fault data using Proportional Aging Reduction(PAR) to consider maintenance effect in time-varying failure rate. In order to product time-varying failure rate, the historical fault data are necessary. However, the maintenance record could be left out in historical data by spot operator's mistake. In this case, the failure rate is produced less than the average failure rate for increasing equipments' life-time by maintenance effect. Hence, it is necessary for new time-varying failure rate to extract maintenance effect from the existing fault data. In this paper, the revision method to reduce equipments' life-time, adversely using PAR among three techniques to consider maintenance effect.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.55 no.11
• /
• pp.476-484
• /
• 2006

The failure prediction and preventive maintenance for the equipment of nuclear power plant area using reliability-centered maintenance have been grown. On the other hand, the maintenance for power distribution system consists of time-based maintenance mainly. In this paper, the new maintenance algorithms for power distribution system are developed considering reliability indices. First of all, Time-varying failure rates are extracted from data accumulated at KEPCO using exponential distribution function and weibull distribution function. Next, based on the extracted failure rate, reliability for real power distribution system is evaluated for applying the effective maintenance algorithm which is the analytic method deciding the maintenance point of time and searching the feeder affecting the specific customer. Also the algorithm deciding the maintenance priority order are presented based on sensitivity analysis and equipment investment plan are analyzed through the presented algorithm at real power distribution system.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.54 no.11
• /
• pp.548-556
• /
• 2005

Reliability evaluation of power distribution system is very important to both power utilities and customers. It present the probabilistic number and duration of interruption such as failure rate, SATDI, SAIFI, and CAIDI. However, it has a fatal weakness at reliability index because of accuracy of failure rate. In this paper, the Time-varying Failure Rate(TFR) of power distribution system equipment is extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) in Korea. For TFR extraction, it is used that the fault data accumulated by KEPCO during 10 years. The TFR is approximated to bathtub curve using the exponential(random failure) and Weibull(aging failure) distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Finally, Probability plot and regression analysis is applied. It is presented that the extracted TFR is more effective and useful than Mean Failure Rate(MfR) through the comparison between TFR and MFR

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.1331-1336
• /
• 2008

This paper suggests a method using Bayesian inference to estimate the parameters of Weibull distribution and acceleration parameters under the condition that the stresses are time-dependent functions. A Bayesian model based on the discrete time approximation is formulated to infer the parameters of interest from the failure data of the virtual tests and a statistical analysis is considered to decide the most probable mean values of the parameters for reasoning of the failure data.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.59 no.2
• /
• pp.154-157
• /
• 2010

In this paper, the Time-varying Failure Rates(TFR) of power distribution system components are extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) and the reliability of power distribution system is evaluated using Mean Failure Rate(MFR) and TFR. The TFR is approximated to bathtub curve using the exponential and Weibull distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Also the reliability of the real power distribution system of Korea is evaluated using the MFR and TFR extracted from real failure data, respectively and the results of each case are compared with each other. As a result, it is proved that the reliability evaluation using the TFR is more realistic than MFR. In addition, it is presented that the application method at power distribution system maintenance and repair using the result of TFR.

• Journal of Industrial Technology
• /
• v.27 no.B
• /
• pp.245-253
• /
• 2007

Failure rate serves as a pivotal role in reliability study. Of all, the constant failure rate is the most popularly used in field exercises. In reality, however, the electrical and electronic parts' life is represented by not only the constant failure rate but the decreasing and/or increasing failure rates. Explicit consideration and incorporation of them into the model development may yield more desirable results. In this study, we built a reliability model for failure rates varying over time intervals and derived well known measures such as probability density function, reliability function, mean life, moments, and mission time. We then evaluated mean life with consideration of the first-year multiplier and compared the results those with constant failure rate. The results given in the study may provide a reference applying for practical decision making.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.10 no.1
• /
• pp.77-84
• /
• 2017

Generally, a time-varying vibration signal is generated in a rotating machine system, and when there is a failure in the rotating machine, the signal contains noise. In this paper, we propose a system consisting of an adaptive predictor and a binary tree filter bank for analyzing time - varying vibration signals with noise. And the vibration signal analyzed results in this system is used for fault diagnosis of the rotating machine. The adaptive predictor of the proposed system predicts the periodic signal components, and the filter bank system decomposes the difference signal between the input signal and the predicted periodic signal into subband. Since each subband signal includes a noise signal component due to a failure, it is possible to diagnose the failure of the using rotary machine. The validity of the proposed vibration signal analysis method is shown in the simulations, where the periodic components cancelled vibrating signals are decomposed to 32 subband, and the signal characteristics related faults are analyzed.

• Proceedings of the KIEE Conference
• /
• 2003.11a
• /
• pp.272-274
• /
• 2003

Distribution system reliability evaluation estimates by approach methods such as Makove modelling or Monte Carlo simulation, equation of state and failure rate that is on one basic data used to these assessment technique is described as probability of average value. because average failure rate equipment device is aged as time goes by but there is shortcoming that such used failure rate does not evaluate thing which is correct in reliability change hereafter. In this paper, failure rate displayed that apply aging to basis equipment device by passing time using Weibull distribution one of life evaluation method and for express aging of component from utility's failure database.